no code implementations • 1 Oct 2023 • Wenjie Liu, Junxiu Chen, Yuxiang Wang, Peipei Gao, Zhibin Lei, Xu Ma
The complex systems with edge computing require a huge amount of multi-feature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational efficiency and save the resource consumption.
no code implementations • 30 Oct 2019 • Hailiang Li, Adele Y. C. Wang, Yang Liu, Du Tang, Zhibin Lei, Wenye Li
The Transformer based neural networks have been showing significant advantages on most evaluations of various natural language processing and other sequence-to-sequence tasks due to its inherent architecture based superiorities.
no code implementations • 30 Nov 2016 • Hailiang Li, Kin-Man Lam, Man-Yau Chiu, Kangheng Wu, Zhibin Lei
The constrained local model (CLM) proposes a paradigm that the locations of a set of local landmark detectors are constrained to lie in a subspace, spanned by a shape point distribution model (PDM).
no code implementations • 21 Nov 2016 • Hailiang Li, Kin-Man Lam, Edmond M. Y. Chiu, Kangheng Wu, Zhibin Lei
In this paper, we present a random-forest based fast cascaded regression model for face alignment, via a novel local feature.